322 lines
15 KiB
Python
Executable File
322 lines
15 KiB
Python
Executable File
#!/usr/bin/env python3
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import json
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import os
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import re
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import openpyxl
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from openpyxl.utils import get_column_letter
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from zipfile import ZipFile, ZIP_DEFLATED
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def update_excel_variables(excel_path):
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"""
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Update the Variables sheet in the Excel file with values from config.json
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and hide forecast sheets that aren't in the calculated years array
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Args:
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excel_path (str): Path to the Excel file to update
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Returns:
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bool: True if successful, False otherwise
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"""
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# Define paths
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script_dir = os.path.dirname(os.path.abspath(__file__))
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config_path = os.path.join(script_dir, 'config.json')
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try:
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# Load config.json
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with open(config_path, 'r') as f:
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config = json.load(f)
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user_data = config.get('user_data', {})
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# Load Excel workbook
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print(f"Opening Excel file: {excel_path}")
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wb = openpyxl.load_workbook(excel_path)
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# Try to access the Variables sheet
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try:
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# First try by name
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sheet = wb['Variables']
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except KeyError:
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# If not found by name, try to access the last sheet
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sheet_names = wb.sheetnames
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if sheet_names:
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print(f"Variables sheet not found by name. Using last sheet: {sheet_names[-1]}")
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sheet = wb[sheet_names[-1]]
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else:
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print("No sheets found in the workbook")
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return False
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# Map config variables to Excel cells based on the provided mapping
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cell_mappings = {
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'B2': user_data.get('store_name', ''),
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'B31': user_data.get('starting_date', ''),
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'B32': user_data.get('duration', 36),
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'B37': user_data.get('open_days_per_month', 0),
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# Convenience store type
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'H37': user_data.get('convenience_store_type', {}).get('stores_number', 0),
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'C37': user_data.get('convenience_store_type', {}).get('monthly_transactions', 0),
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# Convert boolean to 1/0 for has_digital_screens
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'I37': 1 if user_data.get('convenience_store_type', {}).get('has_digital_screens', False) else 0,
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'J37': user_data.get('convenience_store_type', {}).get('screen_count', 0),
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'K37': user_data.get('convenience_store_type', {}).get('screen_percentage', 0),
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# Convert boolean to 1/0 for has_in_store_radio
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'M37': 1 if user_data.get('convenience_store_type', {}).get('has_in_store_radio', False) else 0,
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'N37': user_data.get('convenience_store_type', {}).get('radio_percentage', 0),
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# Minimarket store type
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'H38': user_data.get('minimarket_store_type', {}).get('stores_number', 0),
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'C38': user_data.get('minimarket_store_type', {}).get('monthly_transactions', 0),
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# Convert boolean to 1/0 for has_digital_screens
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'I38': 1 if user_data.get('minimarket_store_type', {}).get('has_digital_screens', False) else 0,
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'J38': user_data.get('minimarket_store_type', {}).get('screen_count', 0),
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'K38': user_data.get('minimarket_store_type', {}).get('screen_percentage', 0),
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# Convert boolean to 1/0 for has_in_store_radio
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'M38': 1 if user_data.get('minimarket_store_type', {}).get('has_in_store_radio', False) else 0,
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'N38': user_data.get('minimarket_store_type', {}).get('radio_percentage', 0),
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# Supermarket store type
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'H39': user_data.get('supermarket_store_type', {}).get('stores_number', 0),
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'C39': user_data.get('supermarket_store_type', {}).get('monthly_transactions', 0),
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# Convert boolean to 1/0 for has_digital_screens
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'I39': 1 if user_data.get('supermarket_store_type', {}).get('has_digital_screens', False) else 0,
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'J39': user_data.get('supermarket_store_type', {}).get('screen_count', 0),
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'K39': user_data.get('supermarket_store_type', {}).get('screen_percentage', 0),
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# Convert boolean to 1/0 for has_in_store_radio
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'M39': 1 if user_data.get('supermarket_store_type', {}).get('has_in_store_radio', False) else 0,
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'N39': user_data.get('supermarket_store_type', {}).get('radio_percentage', 0),
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# Hypermarket store type
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'H40': user_data.get('hypermarket_store_type', {}).get('stores_number', 0),
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'C40': user_data.get('hypermarket_store_type', {}).get('monthly_transactions', 0),
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# Convert boolean to 1/0 for has_digital_screens
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'I40': 1 if user_data.get('hypermarket_store_type', {}).get('has_digital_screens', False) else 0,
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'J40': user_data.get('hypermarket_store_type', {}).get('screen_count', 0),
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'K40': user_data.get('hypermarket_store_type', {}).get('screen_percentage', 0),
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# Convert boolean to 1/0 for has_in_store_radio
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'M40': 1 if user_data.get('hypermarket_store_type', {}).get('has_in_store_radio', False) else 0,
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'N40': user_data.get('hypermarket_store_type', {}).get('radio_percentage', 0),
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# On-site channels
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'B43': user_data.get('website_visitors', 0),
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'B44': user_data.get('app_users', 0),
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'B45': user_data.get('loyalty_users', 0),
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# Off-site channels
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'B49': user_data.get('facebook_followers', 0),
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'B50': user_data.get('instagram_followers', 0),
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'B51': user_data.get('google_views', 0),
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'B52': user_data.get('email_subscribers', 0),
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'B53': user_data.get('sms_users', 0),
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'B54': user_data.get('whatsapp_contacts', 0)
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}
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# Update the cells
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for cell_ref, value in cell_mappings.items():
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try:
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# Force the value to be set, even if the cell is protected or has data validation
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cell = sheet[cell_ref]
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cell.value = value
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print(f"Updated {cell_ref} with value: {value}")
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except Exception as e:
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print(f"Error updating cell {cell_ref}: {e}")
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# Save the workbook with variables updated
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print("Saving workbook with updated variables...")
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wb.save(excel_path)
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# Get the calculated years array from config
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starting_date = user_data.get('starting_date', '')
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duration = user_data.get('duration', 36)
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calculated_years = []
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# Import datetime at the module level to avoid scope issues
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import datetime
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from dateutil.relativedelta import relativedelta
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# Calculate years array based on starting_date and duration
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try:
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# Try to parse the date, supporting both dd/mm/yyyy and dd.mm.yyyy formats
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if starting_date:
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if '/' in str(starting_date):
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day, month, year = map(int, str(starting_date).split('/'))
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elif '.' in str(starting_date):
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day, month, year = map(int, str(starting_date).split('.'))
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elif '-' in str(starting_date):
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# Handle ISO format (yyyy-mm-dd)
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date_parts = str(starting_date).split('-')
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if len(date_parts) == 3:
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year, month, day = map(int, date_parts)
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else:
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# Default to current date if format is not recognized
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current_date = datetime.datetime.now()
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year, month, day = current_date.year, current_date.month, current_date.day
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elif isinstance(starting_date, datetime.datetime):
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day, month, year = starting_date.day, starting_date.month, starting_date.year
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else:
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# Default to current date if format is not recognized
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current_date = datetime.datetime.now()
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year, month, day = current_date.year, current_date.month, current_date.day
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# Create datetime object for starting date
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start_date = datetime.datetime(year, month, day)
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# Calculate end date (starting date + duration months - 1 day)
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end_date = start_date + relativedelta(months=duration-1)
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# Create a set of years (to avoid duplicates)
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years_set = set()
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# Add starting year
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years_set.add(start_date.year)
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# Add ending year
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years_set.add(end_date.year)
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# If there are years in between, add those too
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for y in range(start_date.year + 1, end_date.year):
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years_set.add(y)
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# Convert set to sorted list
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calculated_years = sorted(list(years_set))
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print(f"Calculated years for sheet visibility: {calculated_years}")
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else:
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# Default to current year if no starting date
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calculated_years = [datetime.datetime.now().year]
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except Exception as e:
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print(f"Error calculating years for sheet visibility: {e}")
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calculated_years = [datetime.datetime.now().year]
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# Update sheet names - replace {store_name} with actual store name
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store_name = user_data.get('store_name', '')
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if store_name:
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# Dictionary to store old sheet name to new sheet name mappings
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sheet_name_mapping = {}
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# Make a copy of the sheet names to avoid modifying during iteration
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sheet_names = wb.sheetnames.copy()
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for sheet_name in sheet_names:
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if '{store_name}' in sheet_name:
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new_sheet_name = sheet_name.replace('{store_name}', store_name)
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# Get the sheet by its old name
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sheet = wb[sheet_name]
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# Set the new title
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sheet.title = new_sheet_name
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# Store the mapping
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sheet_name_mapping[sheet_name] = new_sheet_name
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print(f"Renamed sheet '{sheet_name}' to '{new_sheet_name}'")
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# Check if this is a forecast sheet and if its year is in the calculated years
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# Forecast sheets have names like "2025 – Forecast {store_name}"
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if "Forecast" in new_sheet_name:
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# Extract the year from the sheet name
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try:
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sheet_year = int(new_sheet_name.split()[0])
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# Hide the sheet if its year is not in the calculated years
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if sheet_year not in calculated_years:
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sheet.sheet_state = 'hidden'
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print(f"Hiding sheet '{new_sheet_name}' as year {sheet_year} is not in calculated years {calculated_years}")
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except Exception as e:
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print(f"Error extracting year from sheet name '{new_sheet_name}': {e}")
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# Save the workbook with renamed and hidden sheets
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wb.save(excel_path)
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# Use direct XML modification to replace all instances of {store_name} in formulas
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print("Using direct XML modification to update all formulas...")
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update_excel_with_direct_xml(excel_path, store_name)
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print(f"Excel file updated successfully: {excel_path}")
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return True
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except Exception as e:
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print(f"Error updating Excel file: {e}")
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return False
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def update_excel_with_direct_xml(excel_path, store_name):
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"""
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Update all references to {store_name} in the Excel file by directly modifying XML
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Args:
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excel_path: Path to the Excel file
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store_name: The store name to replace {store_name} with
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Returns:
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bool: True if successful, False otherwise
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"""
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try:
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print(f"Using direct XML modification to replace '{{store_name}}' with '{store_name}'...")
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# Create a temporary file for modification
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temp_dir = os.path.dirname(os.path.abspath(excel_path))
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temp_file = os.path.join(temp_dir, f"_temp_{os.path.basename(excel_path)}")
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# Make a copy of the original file
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import shutil
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shutil.copy2(excel_path, temp_file)
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# Count of replacements
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total_replacements = 0
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# Process the Excel file - use a safer approach
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# First read all files from the zip
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files_data = {}
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with ZipFile(excel_path, 'r') as zip_ref:
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for item in zip_ref.infolist():
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files_data[item.filename] = (zip_ref.read(item.filename), item)
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# Modify the content
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for filename, (content, item) in files_data.items():
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# Only modify XML files that might contain formulas or text
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if filename.endswith('.xml') or filename.endswith('.rels'):
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# Skip sheet8.xml which is the Variables sheet (based on common Excel structure)
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if 'sheet8.xml' in filename:
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print(f"Skipping Variables sheet: {filename}")
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continue
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# Convert to string for text replacement
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try:
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text_content = content.decode('utf-8')
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# Check if this file contains our placeholder
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if '{store_name}' in text_content:
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# Count occurrences before replacement
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occurrences = text_content.count('{store_name}')
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total_replacements += occurrences
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# Replace all instances of {store_name} with the actual store name
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modified_content = text_content.replace('{store_name}', store_name)
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# Convert back to bytes
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files_data[filename] = (modified_content.encode('utf-8'), item)
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print(f"Replaced {occurrences} instances of '{{store_name}}' in {filename}")
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except UnicodeDecodeError:
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# Not a text file, leave as is
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pass
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# Write the modified zip file
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with ZipFile(temp_file, 'w', ZIP_DEFLATED) as zip_out:
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for filename, (content, item) in files_data.items():
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zip_out.writestr(filename, content)
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# Replace the original file with the modified one
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shutil.move(temp_file, excel_path)
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print(f"Total replacements: {total_replacements}")
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return True
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except Exception as e:
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print(f"Error updating Excel file with direct XML modification: {e}")
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import traceback
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traceback.print_exc()
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return False
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if __name__ == "__main__":
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# For testing purposes
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import sys
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if len(sys.argv) > 1:
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excel_path = sys.argv[1]
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update_excel_variables(excel_path)
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else:
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print("Please provide the path to the Excel file as an argument")
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